b'Quanming Yao'

research

∙ 09/08/2023

Unleashing the Power of Graph Learning through LLM-based Autonomous Agents

Graph structured data are widely existed and applied in the real-world a...

0 Lanning Wei, et al. ∙

research

∙ 06/15/2023

On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation

Although powerful graph neural networks (GNNs) have boosted numerous rea...

0 Zhanke Zhou, et al. ∙

research

∙ 06/13/2023

Automated 3D Pre-Training for Molecular Property Prediction

Molecular property prediction is an important problem in drug discovery ...

0 Xu Wang, et al. ∙

research

∙ 06/06/2023

ColdNAS: Search to Modulate for User Cold-Start Recommendation

Making personalized recommendation for cold-start users, who only have a...

0 Shiguang Wu, et al. ∙

research

∙ 03/22/2023

Logical Expressiveness of Graph Neural Network for Knowledge Graph Reasoning

Graph Neural Networks (GNNs) have been recently introduced to learn from...

0 Haiquan Qiu, et al. ∙

research

∙ 03/01/2023

Combating Exacerbated Heterogeneity for Robust Models in Federated Learning

Privacy and security concerns in real-world applications have led to the...

0 Jianing Zhu, et al. ∙

research

∙ 02/17/2023

Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification

In recent years, Graph Neural Networks (GNNs) have been popular in the g...

0 Lanning Wei, et al. ∙

research

∙ 02/10/2023

Improving Zero-Shot Coordination Performance Based on Policy Similarity

Over these years, multi-agent reinforcement learning has achieved remark...

0 Lebin Yu, et al. ∙

research

∙ 11/20/2022

Enhancing Intra-class Information Extraction for Heterophilous Graphs: One Neural Architecture Search Approach

In recent years, Graph Neural Networks (GNNs) have been popular in graph...

0 Lanning Wei, et al. ∙

research

∙ 10/30/2022

Search to Pass Messages for Temporal Knowledge Graph Completion

Completing missing facts is a fundamental task for temporal knowledge gr...

0 Zhen Wang, et al. ∙

research

∙ 09/27/2022

Searching a High-Performance Feature Extractor for Text Recognition Network

Feature extractor plays a critical role in text recognition (TR), but cu...

0 Hui Zhang, et al. ∙

research

∙ 08/14/2022

DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction

Spatiotemporal activity prediction, aiming to predict user activities at...

0 Yinfeng Li, et al. ∙

research

∙ 07/24/2022

AutoWeird: Weird Translational Scoring Function Identified by Random Search

Scoring function (SF) measures the plausibility of triplets in knowledge...

0 Hansi Yang, et al. ∙

research

∙ 07/13/2022

Graph Property Prediction on Open Graph Benchmark: A Winning Solution by Graph Neural Architecture Search

Aiming at two molecular graph datasets and one protein association subgr...

0 Xu Wang, et al. ∙

research

∙ 05/30/2022

Learning Adaptive Propagation for Knowledge Graph Reasoning

Due to the success of Graph Neural Networks (GNNs) in learning from grap...

0 Yongqi Zhang, et al. ∙

research

∙ 05/06/2022

Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization

Nonconvex regularization has been popularly used in low-rank matrix lear...

2 Quanming Yao, et al. ∙

research

∙ 05/05/2022

KGTuner: Efficient Hyper-parameter Search for Knowledge Graph Learning

While hyper-parameters (HPs) are important for knowledge graph (KG) lear...

0 Yongqi Zhang, et al. ∙

research

∙ 04/06/2022

Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020

Graph structured data is ubiquitous in daily life and scientific areas a...

3 Zhen Xu, et al. ∙

research

∙ 12/15/2021

LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization

Federated optimization (FedOpt), which targets at collaboratively traini...

0 Huiming Chen, et al. ∙

research

∙ 10/30/2021

Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification

Short text classification is a fundamental task in natural language proc...

2 Yaqing Wang, et al. ∙

research

∙ 08/24/2021

Pooling Architecture Search for Graph Classification

Graph classification is an important problem with applications across ma...

0 Lanning Wei, et al. ∙

research

∙ 08/20/2021

TabGNN: Multiplex Graph Neural Network for Tabular Data Prediction

Tabular data prediction (TDP) is one of the most popular industrial appl...

0 Xiawei Guo, et al. ∙

research

∙ 08/13/2021

Knowledge Graph Reasoning with Relational Directed Graph

Reasoning on the knowledge graph (KG) aims to infer new facts from exist...

0 Yongqi Zhang, et al. ∙

research

∙ 07/01/2021

AutoSF+: Towards Automatic Scoring Function Design for Knowledge Graph Embedding

Scoring functions, which measure the plausibility of triples, have becom...

0 Yongqi Zhang, et al. ∙

research

∙ 06/14/2021

Efficient Data-specific Model Search for Collaborative Filtering

Collaborative filtering (CF), as a fundamental approach for recommender ...

0 Chen Gao, et al. ∙

research

∙ 04/22/2021

Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding

The scoring function, which measures the plausibility of triplets in kno...

0 Shimin Di, et al. ∙

research

∙ 04/21/2021

Searching to Sparsify Tensor Decomposition for N-ary Relational Data

Tensor, an extension of the vector and matrix to the multi-dimensional c...

0 Shimin Di, et al. ∙

research

∙ 04/20/2021

Role-Aware Modeling for N-ary Relational Knowledge Bases

N-ary relational knowledge bases (KBs) represent knowledge with binary a...

0 Yu Liu, et al. ∙

research

∙ 04/14/2021

Search to aggregate neighborhood for graph neural network

Recent years have witnessed the popularity and success of graph neural n...

0 Huan Zhao, et al. ∙

research

∙ 01/04/2021

Tensorizing Subgraph Search in the Supernet

Recently, a special kind of graph, i.e., supernet, which allows two node...

0 Hansi Yang, et al. ∙

research

∙ 11/16/2020

Decoupling Representation and Classifier for Noisy Label Learning

Since convolutional neural networks (ConvNets) can easily memorize noisy...

0 Hui Zhang, et al. ∙

research

∙ 11/09/2020

A Survey of Label-noise Representation Learning: Past, Present and Future

Classical machine learning implicitly assumes that labels of the trainin...

0 Bo Han, et al. ∙

research

∙ 11/09/2020

Graph Neural Network with Automorphic Equivalence Filters

Graph neural network (GNN) has recently been established as an effective...

0 Fengli Xu, et al. ∙

research

∙ 10/24/2020

Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration

Non-local low-rank tensor approximation has been developed as a state-of...

0 Wei He, et al. ∙

research

∙ 10/24/2020

Efficient, Simple and Automated Negative Sampling for Knowledge Graph Embedding

Negative sampling, which samples negative triplets from non-observed one...

0 Yongqi Zhang, et al. ∙

research

∙ 09/07/2020

Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering

Negative sampling approaches are prevalent in implicit collaborative fil...

0 Jingtao Ding, et al. ∙

research

∙ 08/26/2020

Simplifying Architecture Search for Graph Neural Network

Recent years have witnessed the popularity of Graph Neural Networks (GNN...

0 Huan Zhao, et al. ∙

research

∙ 08/14/2020

Efficient Low-Rank Matrix Learning by Factorizable Nonconvex Regularization

Matrix learning is at the core of many machine learning problems. To enc...

8 Yaqing Wang, et al. ∙

research

∙ 07/08/2020

Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases

With the rapid development of knowledge bases (KBs), link prediction tas...

0 Yu Liu, et al. ∙

research

∙ 03/14/2020

Efficient Backbone Search for Scene Text Recognition

Scene text recognition (STR) is very challenging due to the diversity of...

0 Hui Zhang, et al. ∙

research

∙ 11/17/2019

Neural Recurrent Structure Search for Knowledge Graph Embedding

Knowledge graph (KG) embedding is a fundamental problem in mining relati...

0 Yongqi Zhang, et al. ∙

research

∙ 11/06/2019

Searching to Exploit Memorization Effect in Learning from Corrupted Labels

Sample-selection approaches, which attempt to pick up clean instances fr...

0 Hansi Yang, et al. ∙

research

∙ 06/28/2019

Searching for Interaction Functions in Collaborative Filtering

Interaction function (IFC), which captures interactions among items and ...

0 Quanming Yao, et al. ∙

research

∙ 05/30/2019

Differentiable Neural Architecture Search via Proximal Iterations

Neural architecture search (NAS) recently attracts much research attenti...

0 Quanming Yao, et al. ∙

research

∙ 05/12/2019

Robust Learning from Noisy Side-information by Semidefinite Programming

Robustness recently becomes one of the major concerns among machine lear...

0 En-Liang Hu, et al. ∙

research

∙ 04/26/2019

AutoKGE: Searching Scoring Functions for Knowledge Graph Embedding

Knowledge graph embedding (KGE) aims to find low dimensional vector repr...

0 Yongqi Zhang, et al. ∙

research

∙ 04/10/2019

Few-shot Learning: A Survey

The quest of `can machines think' and `can machines do what human do' ar...

0 Yaqing Wang, et al. ∙

research

∙ 12/16/2018

NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding

Knowledge Graph (KG) embedding is a fundamental problem in data mining r...

0 Yongqi Zhang, et al. ∙

research

∙ 12/11/2018

Non-local Meets Global: An Integrated Paradigm for Hyperspectral Denoising

Non-local low-rank tensor approximation has been developed as a state-of...

6 Wei He, et al. ∙

research

∙ 11/23/2018

Privacy-preserving Transfer Learning for Knowledge Sharing

In many practical machine-learning applications, it is critical to allow...

8 Xiawei Guo, et al. ∙

Quanming Yao

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